We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to han...
?Mining association rules on large data sets has received considerable attention in recent years. Association rules are useful for determining correlations between attributes of a ...
—In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions under a single minim...
Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng, C...
Abstract. Association rule mining algorithms such as Apriori were originally developed to automatically detect patterns in sales transactions and were later on also successfully ap...
Data mining is an interactive and iterative process. Users issue series of similar queries until they receive satisfying results, yet currently available data mining systems do not...